Analysis of risk factors for cardiovascular events and construction of a nomogram prediction model in patients undergoing long-term peritoneal dialysis
10.19405/j.cnki.issn1000–1492.2026.04.021
- VernacularTitle:长期腹膜透析患者并发心血管事件的危险因素分析及其列线图预测模型构建
- Author:
Xinyuan ZHOU
1
;
Yuxin JIANG
2
;
Xiaoxia WANG
1
;
Xiangjie YANG
1
;
Runzhe ZHOU
1
;
Yuqing MENG
1
;
Dingxin ZHANG
3
;
Jin ZHANG
2
;
Ying WANG
1
Author Information
1. Department of Biostatistics of Epidemiology， School of Public Health， Anhui Medical University， Hefei 230032
2. Dept of Nephropathy
3. Cardiac Imaging Center， The First Affiliated Hospital of Anhui Medical University， Hefei 230022
- Publication Type:Journal Article
- Keywords:
peritoneal dialysis;
cardiac diastolic function;
cardiovascular events;
nomogram;
prospective cohort study
- From:
Acta Universitatis Medicinalis Anhui
2026;61(4):748-757
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo analyze the risk factors for long-term cardiovascular events in patients undergoing long-term peritoneal dialysis （PD）， and to construct and validate a visual nomogram prediction model based on multiple parameters. MethodsA prospective cohort study was conducted， consecutively enrolling 248 maintenance PD patients （dialysis duration ≥ 3 months）. Demographic characteristics， clinical indicators， laboratory parameters， and echocardiographic indices （including left ventricular ejection fraction ［LVEF］， ratio of early diastolic mitral inflow velocity to early diastolic mitral annular velocity （E/e’）， etc.） were collected. The composite endpoint was defined as the occurrence of cardiovascular events or cardiovascular death， with non-cardiovascular death as the competing risk and loss to follow-up or the end of follow-up as censoring events. Fine-Gray competing risks model was used to screen independent predictors， based on which a nomogram model was constructed. Internal validation was performed using the Bootstrap method （1 000 resamplings）， and the concordance index （C-index） and time-dependent receiver operating characteristic （time-dependent ROC） curve were calculated to evaluate the model performance. ResultsWith a median follow-up of 29 months （interquartile range： 24–35 months）， 88 patients （35.48%） reached the composite endpoint， including 80 cases of cardiovascular events and 8 cases of cardiovascular death， and 4 patients died of non-cardiovascular causes. Multivariate Fine-Gray analysis revealed that age， diabetes mellitus， hemoglobin （HGB） level and E/e' ratio were independent influencing factors of the composite endpoint. Specifically， each 1-year increase in age was associated with a 3.0% increase in the risk of the composite endpoint （HR=1.030， P=0.006）； patients with diabetes mellitus had a 167.9% higher risk compared with non-diabetic patients （HR=2.679， P=0.007）； each 1g/L increase in HGB level contributed to a 1.5% reduction in the risk （HR=0.985， P=0.003）； and each 0.1 increase in E/e' ratio led to a 7.2% increase in the risk （HR=1.072， P=0.045）. The nomogram model had a C-index of 0.76 （95% CI： 0.698–0.820）， and the AUC of the time-dependent ROC curve reached 0.849 at 23 months of follow-up. ConclusionIncreased age， complicated with diabetes mellitus， decreased HGB， and elevated E/e' ratio are independent risk factors of long-term occurrence of cardiovascular events and cardiovascular death in patients undergoing long-term PD. The nomogram model constructed based on the above variables has good predictive value and clinical applicability， which can provide a reference for cardiovascular risk stratification and individualized intervention in long-term PD patients.
